Energy Savings in Renewable Integrated Distribution Network and Impact of Storage Devices
Abstract
Energy loss reduction is a significant issue for Renewable energy planning in the Distribution system. The high penetration of wind and solar became the primary task for the optimal size of energy storage to support the power mismatch. In the present work, energy savings have been obtained in a renewable integrated distribution system. The impact of the energy storage device has also been evaluated. The main contribution of this paper is:
(i) Optimal location of DGs and battery are obtained by solving single and multi-objective functions.
(ii) Determination of DG and battery size for loss savings.
(iii) Impact of battery energy storage device on loss profile and total cost of the system.
The simulation results of the test system have been compared with other existing results
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Introduction
The intermittent behaviour of renewable energy generation has become an essential issue for power deficiency in the distribution network. Therefore, the optimal economical operation for storage devices has to be analysed for supporting power mismatch. The losses along the distribution system are much higher with a higher value of R/X component of the line as compares to the transmission system. Therefore, the loss minimization in distribution system has become an essential issue. Many of the utilities have been used to compensate for the loss in the distribution network. Therefore, the location and sizing of DGs is the major issue in the distribution network. The co-ordination of energy saving with the overall cost of the system is another issue in the system.
A lot of literature is available for optimal placement of DGs to minimize the power loss and voltage deviations in a network. Authors in [1] presented the annual energy loss minimization with the integration of DGs in the network. The optimal DG placement using Stud Krill herd Algorithm (SKHA) for the radial distribution system in [2]. The population-based Gbestguided Artificial Bee Colony (GABC) optimization algorithm has used to minimize the power loss and determine the impact of shunt capacitor with DG placement [3]. Many of the literature is based on the nature-inspired algorithm. In this way, the optimal location of DG has been obtained by using Dragonfly algorithm [4]. An improved particle swarm optimization has been used for the installation of DG in Microgrid (MG) system [5]. The analytical representations are used to obtain the size of DG at various locations for total loss minimisation. The loss saving equations was also represented in [6]. The different types of voltage-dependent loads and a separate line XR ratios have taken into account to study the distribution load flow [7]. Murty et al. [8] have considered the multi-objective based optimization problem for the uncertainty nature of renewable power generation. The reactive power support has also been done using the installation of DG location in [9]. The optimal power factor has considered for the position of DG to minimize the power loss using PSO algorithm by Kansal et al. [10]. The Mixed Integer Non-Linear Programming (MINLP) formulation has introduced in [11] for loss minimization.
Conclusion
This paper represents the hybrid PSO and GAMS optimization using MATLAB and GAMS interfacing to solve the multiobjective problem. This study provides the optimal sizing and siting of battery storage with the integration of renewable sources to minimize the Daily energy loss and cost of the system also. The proposed hybrid algorithm has solved in two parts. (i) In the first part, the PSO algorithm, along with a combined dispatch strategy, has been addressed to obtain the location of DGs and battery storage. (ii) The MINLP algorithm in GAMS has been solved to get the size of DGs and battery storage.
The best combination for economical operation and loss minimization obtained is PV-based, wind-based, diesel-based DG + battery storage.